Armando Sousa

122 papers receiving 983 citations

Peers

Armando Sousa
Comparison fields: 5 of 104
  • Computer Vision and Pattern Recognition 377
  • Geology 69
  • Aerospace Engineering 234
  • Industrial and Manufacturing Engineering 96
  • Environmental Engineering 127
Replace Miguel Torres‐Torriti with:
Miguel Torres‐Torriti Chile
Fernando Santos Osório Brazil
Juan Jesús Roldán Spain
Annalisa Milella Italy
Milena F. Pinto Brazil
Paulo Costa Portugal
Anthony Mandow Spain
Francesco Picariello Italy
Guangming Xiong China
Antoni Grau Spain
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Citations per year

Countries citing papers authored by Armando Sousa

Since Specialization
Citations

This map shows the geographic impact of Armando Sousa's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Armando Sousa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Armando Sousa more than expected).

Fields of papers citing papers by Armando Sousa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Armando Sousa. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Armando Sousa. The network helps show where Armando Sousa may publish in the future.

Co-authors

The 25 scholars most cited alongside Armando Sousa, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Armando Sousa Line = papers co-authored together Armando Sousa links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 134 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019102
2 2020101
3 202056
4 201036
5 200535
6 202033
7 202129
8 201524
9 202222
10 200822
11 202121
12 201920
13 202218
14 202017
15 202516
16 201515
17 201515
18 202114
19 201713
20 201813

About Armando Sousa

Armando Sousa is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Control and Systems Engineering, Biomedical Engineering and Mechanical Engineering, having authored 134 papers that have together received 1.0k indexed citations. Recurring topics across this work include Robotics and Sensor-Based Localization (33 papers), Robotic Path Planning Algorithms (18 papers), Smart Agriculture and AI (11 papers), Remote Sensing and LiDAR Applications (10 papers), Robotics and Automated Systems (10 papers), Teaching and Learning Programming (9 papers), 3D Surveying and Cultural Heritage (9 papers) and Advanced Image and Video Retrieval Techniques (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (377 citations), Geology (69 citations), Aerospace Engineering (234 citations), Industrial and Manufacturing Engineering (96 citations) and Environmental Engineering (127 citations). Armando Sousa has collaborated with scholars based in Portugal, Germany and United States. Frequent co-authors include Filipe Neves dos Santos, André Aguiar, Luís Paulo Reis, Héber Sobreira, Germano Veiga, Carlos M. Costa, José Boaventura‐Cunha, Luís Santos, António Paulo Moreira and Vítor Filipe. Their work appears in journals such as Applied Sciences, Robotics, IEEE Access, International journal of engineering education and Robotics and Autonomous Systems.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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